from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 13.0 | 57.710617 |
| daal4py_KNeighborsClassifier | 0.0 | 3.0 | 41.437401 |
| KNeighborsClassifier_kd_tree | 0.0 | 6.0 | 58.695523 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 52.008240 |
| KMeans_tall | 0.0 | 1.0 | 42.583256 |
| daal4py_KMeans_tall | 0.0 | 1.0 | 20.514885 |
| KMeans_short | 0.0 | 0.0 | 20.296545 |
| daal4py_KMeans_short | 0.0 | 0.0 | 9.687651 |
| LogisticRegression | 0.0 | 1.0 | 5.602987 |
| daal4py_LogisticRegression | 0.0 | 0.0 | 58.531436 |
| Ridge | 0.0 | 0.0 | 0.972541 |
| daal4py_Ridge | 0.0 | 0.0 | 0.660734 |
| total | 0.0 | 32.0 | 8.778553 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.144 | 0.003 | 1000000 | 1000000 | 100 | brute | -1 | 1 | NaN | NaN | 0.484 | 0.001 | 0.297 | 0.001 | See |
| 1 | KNeighborsClassifier | predict | 0.168 | 0.019 | 1000000 | 1 | 100 | brute | -1 | 1 | 1.0 | 0.0 | 0.090 | 0.004 | 1.860 | 0.015 | See |
| 2 | KNeighborsClassifier | predict | 26.566 | 1.048 | 1000000 | 1000 | 100 | brute | -1 | 1 | 1.0 | 0.0 | 2.195 | 0.038 | 12.106 | 0.002 | See |
| 3 | KNeighborsClassifier | fit | 0.141 | 0.003 | 1000000 | 1000000 | 100 | brute | -1 | 5 | NaN | NaN | 0.503 | 0.005 | 0.280 | 0.001 | See |
| 4 | KNeighborsClassifier | predict | 0.180 | 0.018 | 1000000 | 1 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 0.090 | 0.002 | 1.999 | 0.011 | See |
| 5 | KNeighborsClassifier | predict | 36.212 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 2.247 | 0.040 | 16.115 | 0.000 | See |
| 6 | KNeighborsClassifier | fit | 0.141 | 0.003 | 1000000 | 1000000 | 100 | brute | -1 | 100 | NaN | NaN | 0.480 | 0.001 | 0.294 | 0.000 | See |
| 7 | KNeighborsClassifier | predict | 0.184 | 0.018 | 1000000 | 1 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 0.087 | 0.001 | 2.121 | 0.010 | See |
| 8 | KNeighborsClassifier | predict | 36.107 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 2.265 | 0.049 | 15.939 | 0.000 | See |
| 9 | KNeighborsClassifier | fit | 0.138 | 0.003 | 1000000 | 1000000 | 100 | brute | 1 | 1 | NaN | NaN | 0.496 | 0.005 | 0.278 | 0.000 | See |
| 10 | KNeighborsClassifier | predict | 0.185 | 0.003 | 1000000 | 1 | 100 | brute | 1 | 1 | 1.0 | 0.0 | 0.092 | 0.003 | 2.006 | 0.001 | See |
| 11 | KNeighborsClassifier | predict | 13.635 | 0.026 | 1000000 | 1000 | 100 | brute | 1 | 1 | 1.0 | 0.0 | 2.211 | 0.051 | 6.168 | 0.001 | See |
| 12 | KNeighborsClassifier | fit | 0.139 | 0.003 | 1000000 | 1000000 | 100 | brute | 1 | 5 | NaN | NaN | 0.484 | 0.001 | 0.288 | 0.000 | See |
| 13 | KNeighborsClassifier | predict | 0.206 | 0.007 | 1000000 | 1 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 0.088 | 0.002 | 2.336 | 0.002 | See |
| 14 | KNeighborsClassifier | predict | 25.124 | 0.102 | 1000000 | 1000 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 2.234 | 0.049 | 11.248 | 0.000 | See |
| 15 | KNeighborsClassifier | fit | 0.140 | 0.001 | 1000000 | 1000000 | 100 | brute | 1 | 100 | NaN | NaN | 0.500 | 0.005 | 0.279 | 0.000 | See |
| 16 | KNeighborsClassifier | predict | 0.198 | 0.002 | 1000000 | 1 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 0.095 | 0.007 | 2.082 | 0.005 | See |
| 17 | KNeighborsClassifier | predict | 25.242 | 0.031 | 1000000 | 1000 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 2.306 | 0.019 | 10.945 | 0.000 | See |
| 18 | KNeighborsClassifier | fit | 0.062 | 0.000 | 1000000 | 1000000 | 2 | brute | -1 | 1 | NaN | NaN | 0.111 | 0.000 | 0.563 | 0.000 | See |
| 19 | KNeighborsClassifier | predict | 0.023 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.008 | 0.002 | 2.941 | 0.060 | See |
| 20 | KNeighborsClassifier | predict | 22.120 | 0.044 | 1000000 | 1000 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.341 | 0.008 | 64.857 | 0.001 | See |
| 21 | KNeighborsClassifier | fit | 0.062 | 0.000 | 1000000 | 1000000 | 2 | brute | -1 | 5 | NaN | NaN | 0.111 | 0.001 | 0.564 | 0.000 | See |
| 22 | KNeighborsClassifier | predict | 0.032 | 0.001 | 1000000 | 1 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.007 | 0.001 | 4.432 | 0.012 | See |
| 23 | KNeighborsClassifier | predict | 32.003 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.340 | 0.004 | 94.148 | 0.000 | See |
| 24 | KNeighborsClassifier | fit | 0.063 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 100 | NaN | NaN | 0.110 | 0.001 | 0.573 | 0.000 | See |
| 25 | KNeighborsClassifier | predict | 0.033 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.007 | 0.001 | 4.845 | 0.013 | See |
| 26 | KNeighborsClassifier | predict | 31.832 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.401 | 0.006 | 79.376 | 0.000 | See |
| 27 | KNeighborsClassifier | fit | 0.062 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 1 | NaN | NaN | 0.111 | 0.000 | 0.557 | 0.000 | See |
| 28 | KNeighborsClassifier | predict | 0.016 | 0.000 | 1000000 | 1 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.006 | 0.000 | 2.493 | 0.002 | See |
| 29 | KNeighborsClassifier | predict | 10.507 | 0.014 | 1000000 | 1000 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.350 | 0.009 | 30.010 | 0.001 | See |
| 30 | KNeighborsClassifier | fit | 0.062 | 0.000 | 1000000 | 1000000 | 2 | brute | 1 | 5 | NaN | NaN | 0.111 | 0.001 | 0.563 | 0.000 | See |
| 31 | KNeighborsClassifier | predict | 0.026 | 0.000 | 1000000 | 1 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.007 | 0.000 | 3.754 | 0.005 | See |
| 32 | KNeighborsClassifier | predict | 20.683 | 0.048 | 1000000 | 1000 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.343 | 0.008 | 60.310 | 0.001 | See |
| 33 | KNeighborsClassifier | fit | 0.062 | 0.000 | 1000000 | 1000000 | 2 | brute | 1 | 100 | NaN | NaN | 0.112 | 0.003 | 0.552 | 0.001 | See |
| 34 | KNeighborsClassifier | predict | 0.026 | 0.000 | 1000000 | 1 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.007 | 0.000 | 3.804 | 0.001 | See |
| 35 | KNeighborsClassifier | predict | 20.635 | 0.025 | 1000000 | 1000 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.404 | 0.012 | 51.026 | 0.001 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 3.339 | 0.025 | 1000000 | 1000000 | 10 | kd_tree | -1 | 1 | NaN | NaN | 0.813 | 0.012 | 4.110 | 0.000 | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 7.387 | 0.257 | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.501 | 0.005 | 1000000 | 1000 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.116 | 0.003 | 4.328 | 0.001 | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 3.357 | 0.033 | 1000000 | 1000000 | 10 | kd_tree | -1 | 5 | NaN | NaN | 0.827 | 0.020 | 4.059 | 0.001 | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 6.885 | 0.174 | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.923 | 0.004 | 1000000 | 1000 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.215 | 0.007 | 4.295 | 0.001 | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 3.319 | 0.027 | 1000000 | 1000000 | 10 | kd_tree | -1 | 100 | NaN | NaN | 0.796 | 0.019 | 4.169 | 0.001 | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.006 | 0.002 | 1000000 | 1 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 7.462 | 0.229 | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 2.959 | 0.017 | 1000000 | 1000 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.612 | 0.009 | 4.836 | 0.000 | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 3.360 | 0.070 | 1000000 | 1000000 | 10 | kd_tree | 1 | 1 | NaN | NaN | 0.788 | 0.008 | 4.266 | 0.001 | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 2.644 | 0.196 | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.819 | 0.004 | 1000000 | 1000 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.117 | 0.006 | 7.006 | 0.003 | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 3.340 | 0.044 | 1000000 | 1000000 | 10 | kd_tree | 1 | 5 | NaN | NaN | 0.829 | 0.025 | 4.032 | 0.001 | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 2.547 | 0.160 | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1.533 | 0.011 | 1000000 | 1000 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.211 | 0.011 | 7.271 | 0.003 | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 3.302 | 0.043 | 1000000 | 1000000 | 10 | kd_tree | 1 | 100 | NaN | NaN | 0.773 | 0.028 | 4.273 | 0.002 | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 2.428 | 0.217 | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 5.000 | 0.054 | 1000000 | 1000 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.617 | 0.009 | 8.104 | 0.000 | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1.389 | 0.005 | 1000000 | 1000000 | 2 | kd_tree | -1 | 1 | NaN | NaN | 0.538 | 0.019 | 2.583 | 0.001 | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 26.121 | 0.645 | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.029 | 0.002 | 1000000 | 1000 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 25.426 | 0.148 | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1.397 | 0.016 | 1000000 | 1000000 | 2 | kd_tree | -1 | 5 | NaN | NaN | 0.531 | 0.017 | 2.633 | 0.001 | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 20.695 | 0.513 | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.033 | 0.004 | 1000000 | 1000 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 28.643 | 0.086 | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1.402 | 0.021 | 1000000 | 1000000 | 2 | kd_tree | -1 | 100 | NaN | NaN | 0.529 | 0.014 | 2.651 | 0.001 | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 23.246 | 0.675 | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.053 | 0.004 | 1000000 | 1000 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.008 | 0.001 | 6.950 | 0.013 | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1.393 | 0.007 | 1000000 | 1000000 | 2 | kd_tree | 1 | 1 | NaN | NaN | 0.534 | 0.011 | 2.607 | 0.000 | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 5.773 | 0.584 | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.026 | 0.000 | 1000000 | 1000 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 24.105 | 0.174 | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1.405 | 0.012 | 1000000 | 1000000 | 2 | kd_tree | 1 | 5 | NaN | NaN | 0.535 | 0.004 | 2.626 | 0.000 | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 5.914 | 0.665 | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.029 | 0.000 | 1000000 | 1000 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 19.324 | 0.072 | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1.415 | 0.019 | 1000000 | 1000000 | 2 | kd_tree | 1 | 100 | NaN | NaN | 0.556 | 0.019 | 2.543 | 0.001 | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 5.630 | 0.599 | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.059 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.009 | 0.002 | 6.431 | 0.054 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 0.683 | 0.022 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.528 | 0.043 | 1.295 | 0.008 | See |
| 1 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.291 | 0.622 | See |
| 2 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.977 | 0.465 | See |
| 3 | KMeans_tall | fit | 0.578 | 0.011 | 1000000 | 1000000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.476 | 0.035 | 1.214 | 0.006 | See |
| 4 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.897 | 0.490 | See |
| 5 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.527 | 0.442 | See |
| 6 | KMeans_tall | fit | 6.903 | 0.126 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 3.181 | 0.038 | 2.170 | 0.000 | See |
| 7 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.651 | 0.426 | See |
| 8 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.170 | 0.223 | See |
| 9 | KMeans_tall | fit | 6.211 | 0.044 | 1000000 | 1000000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 2.984 | 0.067 | 2.081 | 0.001 | See |
| 10 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.596 | 0.609 | See |
| 11 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.994 | 0.223 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 0.364 | 0.018 | 10000 | 10000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 22.0 | NaN | 29.0 | NaN | 0.115 | 0.003 | 3.157 | 0.003 | See |
| 1 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.102 | 0.550 | See |
| 2 | KMeans_short | predict | 0.001 | 0.001 | 10000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.302 | 0.288 | See |
| 3 | KMeans_short | fit | 0.142 | 0.004 | 10000 | 10000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.053 | 0.005 | 2.681 | 0.009 | See |
| 4 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.760 | 0.586 | See |
| 5 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.058 | 0.067 | See |
| 6 | KMeans_short | fit | 0.877 | 0.028 | 10000 | 10000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 20.0 | NaN | 18.0 | NaN | 0.434 | 0.024 | 2.018 | 0.004 | See |
| 7 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.894 | 0.275 | See |
| 8 | KMeans_short | predict | 0.007 | 0.003 | 10000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 4.701 | 0.249 | See |
| 9 | KMeans_short | fit | 0.247 | 0.031 | 10000 | 10000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 23.0 | NaN | 24.0 | NaN | 0.206 | 0.022 | 1.200 | 0.027 | See |
| 10 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.947 | 0.271 | See |
| 11 | KMeans_short | predict | 0.007 | 0.003 | 10000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 4.992 | 0.273 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 11.974 | 0.113 | 1000000 | 1000000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 12.049 | 0.068 | 0.994 | 0.000 | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.589 | 1.390 | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 1.191 | 0.182 | See |
| 3 | LogisticRegression | fit | 0.810 | 0.017 | 1000 | 1000 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [26] | 0.863 | 0.022 | 0.939 | 0.001 | See |
| 4 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.002 | 0.002 | 0.081 | 1.663 | See |
| 5 | LogisticRegression | predict | 0.002 | 0.000 | 1000 | 100 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.003 | 0.000 | 0.562 | 0.038 | See |
Shared hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 0.039 | 0.001 | 1000 | 1000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.023 | 0.003 | 1.687 | 0.015 | See |
| 1 | Ridge | predict | 0.000 | 0.000 | 1000 | 1 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.642 | 1.130 | See |
| 2 | Ridge | predict | 0.000 | 0.000 | 1000 | 100 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.711 | 0.356 | See |
| 3 | Ridge | fit | 0.008 | 0.000 | 10000 | 10000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.004 | 0.002 | 2.181 | 0.206 | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 10000 | 1 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.643 | 1.062 | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 10000 | 1000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.724 | 0.402 | See |
Shared hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | False |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
{
"system_info": {
"python": "3.8.8 | packaged by conda-forge | (default, Feb 20 2021, 16:22:27) [GCC 9.3.0]",
"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1046-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
"pip": "21.1",
"setuptools": "49.6.0.post20210108",
"sklearn": "0.24.1",
"numpy": "1.20.2",
"scipy": "1.6.2",
"Cython": null,
"pandas": "1.2.4",
"matplotlib": null,
"joblib": "1.0.1",
"threadpoolctl": "2.1.0"
},
"threadpool_info": [
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libopenblasp-r0.3.12.so",
"prefix": "libopenblas",
"user_api": "blas",
"internal_api": "openblas",
"version": "0.3.12",
"num_threads": 2,
"threading_layer": "pthreads"
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libgomp.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
"num_threads": 2
}
],
"cpu_count": 2
}